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Field
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academic assignments at the chair What we look for in you Completed master’s degree in computer science, transportation, or related engineering fields Solid background in generative AI, machine learning, and
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machine learning tools for the efficient analysis of the experimental data. For more information, visit our web page www.soft-matter.uni-tuebingen.de We are looking for a motivated PhD student to contribute
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analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with a strong team
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, agricultural sciences with a focus in economics, or related disciplines - strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, sta-tistics, machine learning
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Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig | Leipzig, Sachsen | Germany | 2 months ago
diagnosis of dementia. This will enable specific therapy to be provided at an early stage. In the project, artificial intelligence / machine learning and new multimodal imaging methods are used to carry out
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interaction-rich scenarios. Ideal applicants will have a strong M.Sc. in machine learning, control, or safety, and hands-on experience with robotics. Apply now: https://lnkd.in/dNjmv835. Deadline: ASAP. We
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Lehrstuhl für Nachhaltige Thermoprozesstechnik und Institut für Industrieofenbau und Wärmetechnik | Aachen, Nordrhein Westfalen | Germany | 9 days ago
. Methodological knowledge in the field of machine learning is an advantage. You have a high level of independence and commitment. You would like to develop and realise your own ideas. You enjoy working in a team
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Your Job: Working with a broad range of imaging modalities (e.g. structural, diffusion-weighted and functional MRI, intracranial EEG) Multi-scale modelling of human brain development Using machine
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cutting-edge methods in chemical, mechanical, and plasma processing of metal ores for a truly circular economy. Correlating experimental, ab initio and multi-scale simulation as well as machine learning
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, integrative biology approach that utilizes human pluripotent stem cell based model systems, high throughput functional genomic screening and big data based machine learning, bridging the scales from genetics